class_docstr: This class returns normalisation and augmentation layers for use with reader objects.
code: def __init__(self, net_param, action_param, task_param):
      self.net_param = net_param
      self.action_param = action_param
      self.task_param = task_param
  
file_path: NiftyNet/niftynet/contrib/preprocessors/preprocessing.py
imports: from niftynet.layer.mean_variance_normalisation import MeanVarNormalisationLayer
  from niftynet.layer.rand_flip import RandomFlipLayer
  from niftynet.layer.rand_rotation import RandomRotationLayer
  from niftynet.layer.rand_spatial_scaling import RandomSpatialScalingLayer
  from niftynet.layer.binary_masking import BinaryMaskingLayer
  from niftynet.layer.histogram_normalisation import HistogramNormalisationLayer
label_desc: Use image node_id 1 to create a new Preprocessing object  with example: obj = Preprocessing(net_param, action_param, task_param)